Pith Number

pith:F2TYA3OD

pith:2026:F2TYA3ODTPZ3CW3CPFCW6NMUB3

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Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

Bin Fu, Diego Adame, Dongchul Kim, Erik Enriquez, Fabian Vazquez, Haoteng Tang, Huimin Li, Jinghao Yang, Jose A. Nunez, Pengfei Gu

Patch-MoE Mamba addresses limitations in Mamba models by using hierarchical patch-ordered scanning and mixture-of-experts fusion for medical image segmentation.

arxiv:2605.17719 v1 · 2026-05-18 · cs.CV

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Claims

C1strongest claim

Experiments on five public polyp segmentation benchmarks and the ISIC 2017/2018 skin lesion segmentation datasets demonstrate the effectiveness and generality of Patch-MoE Mamba.

C2weakest assumption

That the hierarchical patch-ordered scanning mechanism preserves local spatial neighborhoods while capturing multi-scale context better than standard pixel-wise directional scanning, as stated in the problem setup for existing Mamba models.

C3one line summary

Patch-MoE Mamba introduces patch-ordered hierarchical scanning and an MoE-based directional fusion module to improve Mamba segmentation models on polyp and skin lesion datasets.

References

22 extracted · 22 resolved · 2 Pith anchors

[1] PraNet: Parallel reverse attention network for polyp segmentation, 2020

[2] Automated polyp detection in colonoscopy videos using shape and context information, 2015

[3] Keep your friends close & enemies farther: Debiasing contrastive learning with spatial priors in 3D radiology images, 2022

[4] Sli2vol+: Segmenting 3D medical images based on an object estimation guided correspondence flow network, 2025

[5] U-Net: Convolutional networks for biomedical image segmentation, 2015

Receipt and verification

First computed	2026-05-20T00:04:54.648587Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2ea7806dc39bf3b15b6279456f35940ef2054260e55599a06a05cb4d497edb51

Aliases

arxiv: 2605.17719 · arxiv_version: 2605.17719v1 · doi: 10.48550/arxiv.2605.17719 · pith_short_12: F2TYA3ODTPZ3 · pith_short_16: F2TYA3ODTPZ3CW3C · pith_short_8: F2TYA3OD

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/F2TYA3ODTPZ3CW3CPFCW6NMUB3 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 2ea7806dc39bf3b15b6279456f35940ef2054260e55599a06a05cb4d497edb51

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "190c563602de92113cc293fa8a8ac671c52139756b21f0fa0217a5e39a1f3b33",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-18T00:42:04Z",
    "title_canon_sha256": "0b7d506370cb588383ecc99f97190ecb5f5cf49080febf55c8251b95bbe84758"
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  "source": {
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    "kind": "arxiv",
    "version": 1
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}